Closed mdelliot closed 1 year ago
Hi,
Have you checked the distribution of the phenotype for the 121 samples analyzed? Note that we recommend running Step 1 on a fairly large set of variants (eg 500K) to get good genome-wide coverage (here you only have 36K).
Hi, I'm trying to run a small test sample for a quantitative trait through step 1 and I cannot get any Output other than the one listed here. Any ideas of what is going wrong? Thank you
Copyright (c) 2020-2022 Joelle Mbatchou, Andrey Ziyatdinov and Jonathan Marchini. Distributed under the MIT License. Compiled with Boost Iostream library. Using Intel MKL with Eigen.
Log of output saved in file : /Regenie/Step1New/MinMAF1pct/QT/regenieRes.log
WARNING: only variants which satisfy both extract/exclude options will be kept. Options in effect: --step 1 \ --bed /Regenie/allQCBAFilter/allQCBAFilter \ --covarFile /Regenie/CovPheno/covariates.txt \ --phenoFile /Regenie/CovPheno/phenotypesQT.txt \ --qt \ --lowmem \ --apply-rint \ --covarColList U1,U2,U3,U4,U5,U6,sex \ --extract /Regenie/allQCBAFilter/snps.pruned.QT.snplist \ --exclude /Regenie/allQCBAFilter/QT.exclude \ --bsize 100 \ --loocv \ --lowmem-prefix /Regenie/Step1New/MinMAF1pct/QT/ \ --out /Regenie/Step1New/MinMAF1pct/QT/regenieRes
Fitting null model
threads : [47]
blocks : [373] for 35900 variants
CV folds : [121]
With the output of:
Level 1 ridge... -on phenotype 1 (C3)...done (86ms)
Output
phenotype 1 (C3) : 0.01 : Rsq = -nan, MSE = -nan<- min value 0.25 : Rsq = -nan, MSE = -nan 0.5 : Rsq = -nan, MSE = -nan 0.75 : Rsq = -nan, MSE = -nan 0.99 : Rsq = -nan, MSE = -nan
and the pred.list file is all -nan